Software Cost Estimating. Acknowledgments

Transcription

1 Software Cost Estimating Techniques for estimating in a software development environment Any sufficiently advanced technology is indistinguishable from magic. - Arthur C. Clarke Unit IV - Module 12 1 Acknowledgments ICEAA is indebted to TASC, Inc., for the development and maintenance of the Cost Estimating Body of Knowledge (CEBoK ) ICEAA is also indebted to Technomics, Inc., for the independent review and maintenance of CEBoK ICEAA is also indebted to the following individuals who have made significant contributions to the development, review, and maintenance of CostPROF and CEBoK Module 12 Software Cost Estimating Lead authors: Belinda J. Nethery, Allison L. Horrigan, Harold van Heeringen Assistant authors: Tara L. Eng, Heather F. Chelson Senior reviewers: Richard L. Coleman, Michael A. Gallo, Fred K. Blackburn Reviewer: Kenneth S. Rhodes Managing editor: Peter J. Braxton Unit IV - Module

2 Unit Index Unit I Cost Estimating Unit II Cost Analysis Techniques Unit III Analytical Methods Unit IV Specialized Costing 11. Manufacturing Cost Estimating 12. Software Cost Estimating - Basic - Advanced Unit V Management Applications Unit IV - Module 12 3 Software Cost Estimating Overview Key Ideas Cost Drivers Size Complexity Capability SLOC vs. ESLOC vs. Function Points Development Methodologies Practical Applications ESLOC Sizing / FP sizing Software Effort Calculation Capability Adjustments Complexity Adjustments Schedule Determination Schedule Compression Factors Analytical Constructs ESLOC Equation COCOMO II CER Equation COCOMO II Schedule CER ISBSG historical data ISBSG formulas Other parametric models Related Topics 2 Costing Techniques Parametric Estimating Regression Analysis 8 3 Unit IV - Module

3 Software Cost Estimating Outline Core Knowledge Software Overview Software Development Approaches Software Cost Drivers Estimating Life Cycle Methodologies Estimating Techniques Applied to Software Challenges in Estimating Software Summary Resources Related and Advanced Topics Unit IV - Module 12 5 Software overview Software is a key component of almost every system including: Custom Developed Software Commercial-Off-The-Shelf (COTS) Software Databases Enterprise Resource Planning (ERP) Tools Software development is both an art and a science, as is estimating software development There are a number of parametric models available in the industry: COCOMO II (Barry Boehm) SLIM (Putnam QSM) SEER-SEM (Galorath) Trueplanning (Pricesystems) ISBSG formulas and CERs Unit IV - Module

4 Software Industry Software project industry: low maturity - Low estimation maturity - No or little formal estimation processes - No or little use of historical data - Customers chose suppliers based on price, not reality Lots of schedule and cost overruns - Standish Chaos reports: Most projects fail or are at least unsuccessful Low customer satisfaction rates - In Europe: only slightly higher than the financial sector Unit IV - Module 12 7 Software project estimation Most of the projects are estimated by experts - Bottom up, task by task effort estimation Usually very optimistic (>30% deviation) - Experts estimate, but other people (juniors) do the job - Forgotten activities (e.g. testscript reviews) - No feedback loop with past projects: experts don t learn - from past estimates and actuals No scenario s: duration, team size, etc. Not objective, transparent, verifiable and repeatable - Not defendable! Easy to push back by stakeholders - No risk assessment (distribution of the estimate) Unit IV - Module

5 Software - What We Do (and Don t) Know Software isn t easy to understand because it s not a tangible item Developing software can be extremely costly and time consuming Chaos has been downgraded Standish Group s 1994 study was revisited in 2000 Examined IT developed software projects Schedule overruns have significantly decreased from 222% over the original time estimates in 1994 down to 63% in 2000 Cost overruns have gone from 189% over the original cost estimates in 1994 down to 45% in the 2000 study Better tools have been created to monitor and control progress Better management processes have emerged Extreme Chaos, copyright 2001 The Standish Group International, Inc. Unit IV - Module 12 9 Software Cost Engineering Not a real profession yet - Consultant software metrics - Estimation officer - Bid specialist Parametric estimates - Functional size measurement size of the software - Productivity rates from historical data or industry data - Parametric estimation tools Objective, repeatable, transparent and verifiable Defendable!! Impossible to push back by stakeholders Risk assesment (distribution of the estimate) Basis of Estimate (BOE) recommended practice by AACE Unit IV - Module

6 Software Development Process The same basic system engineering steps are followed when developing software as when developing a hardware system Systems today usually consist of both hardware and software. System Engineering Steps for Software Step 1: System Requirements and Design (both hardware and software) Step 2: Software Requirements Analysis Step 3: Software Preliminary and Detailed Design Step 4: Code and Unit Test Step 5: Unit Integration and Test Step 6: Software System Test Step 7: System Test (both hardware and software) MIL STD 498, Software Development and Documentation, December, 1994 These steps provide a framework for structuring the Software WBS Unit IV - Module Coding is equivalent to building a piece of hardware WBS for Software Programs Sample Partial WBS This is an example, each WBS will have a unique mapping 1.1 System SE/PM (Includes Step 1) 1.2 System SIT&E (Includes Step 7) 1.3 Hardware 1.4 Software Build SE/PM (Includes Step 2 & 3) SIT&E (Includes Step 5 & 6) CSCI CSCI CSC 1 (Includes Step 4) CSC Build Build 3 Etc. It is important that the cost analyst understand the content associated with a particular cost Framework to break large projects into product oriented elements and processes Used as a foundation for cost estimating, schedule planning, progress tracking, risk monitoring and many other management functions Dept of Defense mandates use of a WBS (guidance in Military Handbook 881A) Industry has no mandated standard; however, use of WBS recommended by IEEE IEEE/EIA , IEEE/EIA Guide, Industry Implementation of International Standard ISO/IEC 12207; 1995, Standard for Information Technology, Software Life Cycle Processes Implementation Consideration, April 1998 Unit IV - Module

7 Cost Drivers Size Complexity Capability Unit IV - Module Cost Drivers Overview Cost Drivers are used to create a Cost Estimating Relationship (CER) between the drivers and the cost Although it is generally agreed that these are the main cost drivers of software, the CERs based on the drivers differ The COCOMO II CER is commonly used COCOMO II CER equation PM Size A Size E n i 1 EM i Where: PM = Person Months A = Constant = 2.94 Size = SLOC in thousands (KSLOC E = Sum of Scale Factors (Economies or Diseconomies of Scale) EM = Effort Multipliers Complexity and Capability Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, 2000 Unit IV - Module

8 Cost Drivers Size 2 Size is the primary cost driver of software development costs Methods of measuring size include 12 Source Lines of Code (SLOC) Equivalent Source Lines of Code (ESLOC) Function Points / COSMIC Function Points Object Points A good assessment of size is critical to a good estimate! Unit IV - Module Source Lines of Code (SLOC) 3 Include executable instructions and data declarations Do not include comments, blanks, and continuation lines Warning: This is just one definition of SLOC, not the definition of SLOC. 2 Can be accurately and consistently counted after completed development with automated counting tools Delivered source lines of code (DSLOC) Prior to development, must be estimated using standard estimating techniques Analogy is the most common Guidelines for Successful Acquisition and Management of Software Intensive Systems: Weapon Systems, Command and Control Systems, Management Information Systems, Version 3.0, Dept of the Air Force, Software Technology Support Center, 2000 Unit IV - Module

9 SLOC Issues Advantages Widely utilized in real-time systems and many legacy IT systems Easily counted; can use automated counters Less subjectivity in counting than with other measures Disadvantages Wide discrepancies occur even with standard definitions Logical vs. physical SLOC counts Driven by language choices Different software languages require a different number of lines of code for same function Does not adequately address COTS-based systems Not of value to customer/business (more slocs is better?!?) Different code counters, different results Only possible to use after project completion Unit IV - Module Counting Reusable Code Software is often a mix of new code and code developed in previous efforts Reused code requires no modification Adapted code requires some amount of redesign, recoding, and retesting Rework may be major or minor Software estimating models are usually based on new lines of developed code Provide input to models on amount of reused/adapted code; or Unit IV - Module Software Engineering Economics, Barry W. Boehm, Prentice Hall, 1981 Calculate equivalent new source lines of code (ESLOC) Warning: There are many terms and conventions to denote code from another source, so defining terms is crucial 9

10 Equivalent Source Lines of Code 4 Equivalent Source Lines of Code (ESLOC) The effective size of reused and adapted code adjusted to its equivalent in new code + The size of the new code The adjustment is based on the additional effort it takes to modify the code for inclusion in the product ESLOC Equation from COCOMO ESLOC = SLOC * [ (40% * % Design Modified ) + (30% *% Code Modified ) + (30% * % Integration & Test ) ] Assumes: - 40% of effort is for design - 30% of effort is for coding - 30% of effort is for test You may have to change percentages for your environment Unit IV - Module Example on the following slide Warning: Beware of claims that no testing will be required. Software Engineering Economics, Barry W. Boehm, Prentice Hall, 1981 ESLOC Example 19 Suppose from the Example Scenario that the code sizes given are Reused and Adapted Code Find the ESLOC given: Total Reused and Adapted Code = 100,000 SLOC CSCI 1 45,000 SLOC; 20% retest CSCI 2 35,000 SLOC; 80% redesign, 100% recode and retest CSCI 3 20,000 SLOC; 50% recode and retest Calculations: ESLOC = SLOC * [ (40% * % Design) + (30% *% Code) + (30% * % Test ) ] CSCI 1 - ESLOC = 45,000 * [(40%*0%)+(30%*0%)+(30%*20%)] = 2,700 CSCI 2 - ESLOC = 35,000 * [(40%*80%)+(30%*100%)+(30%*100%)] = 32,200 CSCI 3 ESLOC = 20,000 * [(40%*0%)+(30%*50%)+(30%*50%)] =6,000 Total ESLOC = 2, , ,000 = 40,900 You may need to adjust the mix of total effort applied to design, code, and test for the project you are estimating. Ask the engineers! Unit IV - Module

11 Code Size Growth Delivered project is bigger than estimated Increase driven by: Poor understanding of requirements initially New requirements added during development Underestimate of required SLOC Code reuse optimism Key is to know the track record and account for expected growth Some commercial tools have options for the confidence level of the size estimates Use industry metrics to adjust Unit IV - Module Warning: Beware requirements creep! Function Points 18 Considers the number of functions being developed based on the requirements specification The requirements of a system can be gathered from: People: The Program s Primary Users. Program Developers, System Analysts, Project Managers Documents: Architecture diagrams, Data models, Detailed design specifications and requirements, Business function/process models, User manuals, Screen prints, Function Point Counting Practices Manual FP Analysis can be performed with as many/few of these documents as long as sufficient understanding can be gained FP Counting Process Determine the Type of FP Count Indentify the Scope and the Boundaries of the Application Function Point Analysis: Introduction and Basic Overview as an Alternative to SLOC-based Estimation. Moore, Tucker. 2010, TASC, Inc. Count the Data Function Types Count the Transaction Function Types Calculate the Unadjusted Function Points (UFP) Determine the Value Adjustment Factor (VAF) Calculate the Adjusted Function Points (AFP) Unit IV - Module

12 IFPUG / NESMA FPA User Transactions Data EI ILF EO EIF EQ Unit IV - Module Functions Transaction Files - Made up of the processes exchanged between the user, the internal files, and the external files External Inputs (EI): User inputs that provide data External Outputs (EO): Output to users such as reports, screens, error message External Inquiries (EQ): Data sent to other applications Each Transaction Function is broken down into File Types Referenced (FTRs) and then into Data Element Types (DETs) Data Functions Made up of the Internal and External resources that affect the system Internal Logical Files (ILF): Online input that results in software response External Interface Files (EIF): Machine readable interfaces used to transmit information to another system (disks and tapes) Each Data Function is broken down into Record Element Types (RETs) and then into Data Element Types (DETs) Software Engineering, A Practitioner s Approach, 3 rd ed, Roger S. Pressman, McGraw Hill, Inc., 1992 Unit IV - Module NEW! 12

13 FP Calculations Tables are used to calculate the number of UFPs EI Table Shared EO & EQ Table UFP Conversion ILF/EIF Table UFP Conversion A Value Adjustment Factor (VAF) is then computed Based on 14 general system characteristics (GSCs) that rate the general functionality of the application being counted by degree of influence (0-5) Using the IFPUG Value Adjustment Equation: VAF = [ (Ci) / 100], where i = is from 1 to 14 representing each GSC The final Function Point Count is obtained by multiplying the VAF times the UAF: FP = UAF * VAF Unit IV - Module Software Metrics, NEW! Function Points Issues Advantages Countable early in the development effort Language/technology independent Extra documentation review Objective, verifiable, repeatable, defendable Disadvantages Subjectivity involved in counting Don t capture non-functional requirements (how SW must perform) or technical and design constraints (how SW will be built) International Function Point Users Group (IFPUG), Provides information and training on how to count and use function points Certified Function Point Specialist (CFPS) certification Software Engineering, A Practitioner s Approach, 3 rd ed, Roger S. Pressman, McGraw Hill, Inc., 1992 Unit IV - Module

14 Function Points early methods NESMA FPA and IFPUG FPA Two almost identical methods Comply to ISO standard for functional size measurement Early measurement: Indicative approach (based on data model only) Unit IV - Module Function Points early methods Estimated FPA Logical files: Low complexity Transactions: Medium complexity Unit IV - Module

15 COSMIC FPA Users Functional Processes Persistent storage Entry Write exit Read Unit IV - Module COSMIC early methods Basis: high level requirements Indicative method: Average functional process based on requirements. E.g. 8 CFP per functional process (calibration needed) Estimated method: Average CFP per size band (S / M / L / XL) Unit IV - Module

16 Size to effort historical data size Risk analysis productivity risks gross hours hours (and costs) Influences measures consequences Unit IV - Module Productivity Prefered: own historical data Based on completed projects in certain technology Measurement and data collection process needed Alternative: industry data / benchmark data Multiple possible sources of data in the industry One independent and open data source: ISBSG Unit IV - Module

17 ISBSG International Software Benchmarking Standards Group Independent and not-for-profit; Full Members are non-profit organizations, like IFPUG, NESMA, GUFPI-ISMA, FiSMA, QESP, DASMA, JFPUG, Swiss-ICT and CESI; Associate members: AEMES (Asociacion Espanola de Metricas de Software), ASSEMI (France); Grows and exploits two repositories of software data: New development projects and enhancements (> 6000 projects); Maintenance and support (> 1200 applications). Everybody can submit project data DCQ on the site / on request (.xls) Anonymous Free benchmark report in return ISBSG Mission: To improve the management of IT resources by both business and government, through the provision and exploitation of public repositories of software engineering knowledge that are standardized, verified, recent and representative of current technologies. All ISBSG data is validated and rated in accordance with its quality guidelines current representative of the industry independent and trusted captured from a range of organization sizes and industries 17

18 ISBSG data In Excel, easy to filter and analyse the data Full control over CER development Unit IV - Module ISBSG formulas, example table C-2.2 Project Duration, estimated from software size only Functional size 1200 FP C from table 0,645 E1 from table 0,378 Duration = C * Size^E1 Duration = 9,4 elapsed months Class C E1 N R2(adj) Median MRE New Development 0,543 0, ,3 0,41 PC 0,507 0, ,33 0,39 Multi 0,589 0, ,28 0,44 4GL 0,507 0, ,36 0,37 New & PC 0,297 0, ,42 0,42 New & Multi 0,423 0, ,33 0,41 New & 3GL 0,645 0, ,27 0,42 New & 4GL 0,239 0, ,4 0,43 Enh & 4GL 0,54 0, ,34 0,36 PC & 3GL 0,468 0, ,36 0,4 Multi & 4GL 0,201 0, ,46 0,4 New & PC & 3GL 0,284 0, ,43 0,42 New & PC & 4GL 0,324 0, ,41 0,32 New & Multi & 3GL 0,558 0, ,33 0,37 New & Multi & 4GL 0,107 0, ,38 0,52 Enh& Multi & 4GL 0,174 0, ,63 0,22 table C-2.2 Project Duration, ICEAA. All estimated rights reserved. from software size only 18

19 Effort (PM) Thousands CEB 09 - Basic Softwrae Cost Estimating Response of Cost to Size Cost increases as size increases The nature of the increase depends on development factors such as the management of communication and coordination Economies of scale occur if: Project big enough to warrant tools purchase Can manage communication and coordination problems Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, Diseconomies of scale occur if: Tools are insufficient Cannot manage communication and coordination problems Unit IV - Module COCOMO II Scale Factors Size (KSLOC) Very Low Low Nominal High Very High Extra High 5 Cost Drivers Complexity Factors that relate to the software itself Language Function (intended use) Hardware Limitations Number of Modules Amount of Integration Percent of New Code Quality of Development (for maintenance) Warning: These are generally assumed to be cost drivers, but this is difficult to show statistically Names and groupings may vary from model to model. PRICE S Users Manual, Price Systems, Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, 2000 Unit IV - Module

20 Complexity Language Vary in complexity from Machine to Very High Order (4GL) Models adjust for differences in language complexity, length, etc. Drives the amount of design vs. code vs. test Object-Oriented languages require more design and less code and test 6 Spoken Language Human Programmer Very High- Level Language Interpreter or Compiler Higher- Order Language Computer Programming Languages HOL Advantages -Easier to read and write -More Human-efficient -More user-friendly -Attuned to modern design methods Assembler Assembler Advantages -More machine efficient -Less application dependent Assembler Language Machine Language 1s and 0s Quantitative Management of Software, Graduate School of Logistics and Acquisition Management, Air Force Institute of Technology, Air University, 1995 Unit IV - Module Complexity Function 7 Function: purpose of software and required reliability Typical Applications include: Statistical/Mathematical String Manipulation Graphical User Interface (GUI) Data Storage and Retrieval Graphical Functions On-line Communications Control Functions Multi-media Real Time Interactive Operating System Warning: This is the PRICE S model definition of the Application (APPL) cost driver - other models will have other unique terminology/definitions Logical Functions PRICE S Users Manual, Price Systems, Unit IV - Module

21 Complexity Other Factors 8 Hardware Limitations: hardware on which software will run may drive the need for more efficient code, requirements uncertainty, schedule delays Number of Modules: drives integration, standardization, communication and coordination Quality of Developed Software (for Maintenance): better software requires less and easier-to-perform maintenance Unit IV - Module Response of Cost to Complexity Cost increases as complexity increases Effort is greatest at the highest levels of complexity Relationship is generally thought to be exponential Product EMs by Rating RELY DATA CPLX RUSE DOCU Very Low Low Nominal High Very High Extra High Platform EMs by Rating Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, Unit IV - Module TIME STOR PVOL Very Low Low Nominal High Very High Extra High 21

22 Cost Drivers Capability Factors that relate to the developers and the development environment Application Experience Skill Schedule Constraints Tools Experience Development Location Warning: These are generally assumed to be cost drivers, but this is difficult to show statistically Warning: For these cost drivers, large projects tend to regress to the mean, relative to the underlying project database Warning: These cost drivers are subjective in nature and so may introduce bias Names and groupings may vary from model to model. PRICE S Users Manual, Price Systems, Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, 2000 Unit IV - Module Capability 9 Overall Skill of Developer: Better skill requires less effort Increased productivity offsets higher cost Experience with the Application: No learning required Experience with Development Tools: No learning required Schedule Constraints may cause developers to: Increase the number of programmers leading to communication problems Minimize requirements analysis and design which leads to more expensive fixes in code and test Limit documentation leading to higher maintenance/reuse costs Development Location: Separation makes communication and coordination more difficult Unit IV - Module

23 Response of Cost to Capability Costs decrease as capability increases Impact is greater between lower and nominal capability Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, Product EMs by Rating Personnel EMs by Rating TOOL SITE SCED Very Low Low Nominal High Very High Extra High ACAP PCAP PCON APEX PLEX LTEX Very Low Low Nominal High Very High Extra High Unit IV - Module Cost Drivers Example Size For the mail order business Example Scenario, suppose the Developer proposes 3 solutions Find the cost for each given: Barebones Solution: 50,000 SLOC 10 Original Solution: 100,000 SLOC Bells & Whistles Solution: 150,000 SLOC 13 Nominal Complexity Nominal Capability Labor Rate $16,000/month fully burdened COCOMO II CER for software dev effort COCOMO II CER PM A Size Where: i 1 PM = Person Months A = Constant = 2.94 Size = KSLOC E = Sum of Scale Factors EM = Effort Multipliers Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, 2000 E n EM i Calculations: 50,000 SLOC 2.94 * * 1 * $16,000 = $3,473, ,000 SLOC 2.94 * * 1 * $16,000 = $7,445, ,000 SLOC 2.94 * * 1 * $16,000 = $11,628,264 Unit IV - Module

24 Cost Drivers Example Complexity For the Example Scenario suppose the 100,000 SLOC solution is chosen, but the complexity of the solution varies Find the cost for each given: Low Complexity: EM = 0.6 Nominal Complexity: EM = 1.0 High Complexity: EM = 3.5 Nominal Capability Labor Rate $16,000/month fully burdened COCOMO II CER for software dev effort COCOMO II CER PM A Size Where: i 1 PM = Person Months A = Constant = 2.94 Size = KSLOC E = Sum of Scale Factors EM = Effort Multipliers Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, 2000 E n EM i Calculations: Low: EAF = * * 0.6 * $16,000 = $4,467,027 Nom: EAF = * * 1.0 * $16,000 = $7,445,045 High: EAF = * * 3.5 * $16,000 = $26,057,657 Unit IV - Module Cost Drivers Example Capability For the Example Scenario suppose the 100,000 SLOC solution is chosen, but the potential programmer capability varies Find the cost for each given: Best Programmers: EM = 0.33 Labor Rate $20,000/month fully burdened Average Programmers : EM = 1.0 Labor Rate $16,000/month fully burdened Junior Programmers: EM = 5.22 Labor Rate $14,000/month fully burdened Nominal Capability COCOMO II CER for software dev effort Calculations: COCOMO II CER PM A Size Where: i 1 PM = Person Months A = Constant = 2.94 Size = KSLOC E = Sum of Scale Factors EM = Effort Multipliers Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, 2000 E n EM i Best: EM = * * 0.33 * $20,000 = $3,071,081 Avg: EM = * * 1.0 * $16,000 = $7,445,045 Jr: EM = * * 5.22 * $14,000 = $34,005,242 Unit IV - Module

25 Schedule Months CEB 09 - Basic Softwrae Cost Estimating Development Schedule 20 Often have to estimate schedule as well as cost Issues Schedule driven by contract or need date not by reality Developers don t have a good understanding of scheduling Schedule vs. Effort Schedule months = Number of calendar months to develop Effort months = Number of calendar months * the number of people working per month (Person Months) Unit IV - Module Schedule Example Let s suppose the Owner wants to know how long the schedule (TDEV) would be with no compression (SCED % = 1.0) for the 100,000 SLOC solution Person Mos vs Schedule Mos (SCED% = 1) Person Months Calculations: TDEV = [3.67*(465) (.28+.2*( )) ] * 1 = months Given: 465 Person months 1 Person month = 152 hrs SCED% = 1.0 (100%) E = COCOMO II CER for schedule Unit IV - Module COCOMO II Schedule CER TDEV = [C*(PM NS ) F ]*SCED% TDEV = [C*(PM NS ) (D+0.2*[E-B]) ]*SCED% Where: TDEV = Calendar time in months E = Sum of Scale factors C = Constant = 3.67 B = Constant = 0.91 D = Constant = 0.28 F = D X (E-B) PM NS = Person Months (un-scaled) SCED% = The amount of schedule compression or stretch-out as a percent of the nominal value Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR,

26 Schedule Compression Example Let s suppose the Owner wants to know the Compression (1-SCED%) the Developer is counting on to meet the 18 month deadline for the 100,000 SLOC solution Given: 18 month Schedule 465 Person months E = COCOMO II CER for schedule Calculations: Where: Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, 2000 Unit IV - Module COCOMO II Schedule CER TDEV = [C*(PM NS ) F ]*SCED% TDEV=[C*(PM NS ) (D+0.2*[E-B]) ]*SCED% TDEV = Calendar time in months F = D X (E-B) C = 3.67 PM NS = Person Months (un-scaled) D = 0.28 E = Sum of Scale factors B = 0.91 SCED% = The amount of schedule compression or stretch-out as a percent of the nominal value TDEV = [3.67*(465) (.28+.2*( )) ] * SCED% = 18 months SCED% = 18 / [3.67*(465) (.28+.2*( )) ] = 66% (1-SCED%) = (1-66%) = 33% Post-Deployment Software Support Like hardware, software has an operational phase Costs must be accounted for in life cycle cost (LCC) Operations and support (O&S) for software termed Post-Deployment Software Support (PDSS) Includes software maintenance Also includes help desk/trouble ticket functions Models only account for software maintenance Other areas need to be addressed outside of model Remember, how well software was originally developed has a major impact on software support costs. You pay in development or you pay in support. Unit IV - Module

27 Software Maintenance 17 Software doesn t degrade or wear out like hardware Use may uncover bugs not addressed in testing When introduced to a new environment, software may break Software Maintenance includes: Corrective: Fixes defects in the code Adaptive: Modifies the software to accommodate changes in the external environment Perfective: Extends the software beyond its original functional requirements For Software, there is overlap between Maintenance and Development Portions of code may need maintenance during development When additional capability is added, Software maintenance can be thought of as a mini-development effort Cost drivers are the same + the quality of the code being maintained Software Engineering, A Practitioner s Approach, 3 rd ed, Roger S. Pressman, McGraw Hill, Inc., 1992 Unit IV - Module Estimating Development Methodologies Waterfall Agile Other Methods Unit IV - Module

28 Development Methodologies A software development methodology is an overall approach to system development Need to understand methodology being used for proper modeling, calibration, and CER development Commonly used methodologies are Waterfall: conventional, theoretical methodology Agile: based on iterative and incremental development Other common methods Incremental: breaks development into clearly-defined, stand alone system increments Evolutionary: built to satisfy requirements as they evolve Spiral: risk based analysis of alternatives approach More detailed information provided in the advanced topics Guidelines for Successful Acquisition and Management of Software Intensive Systems: Weapon Systems, Command and Control Systems, Management Information Systems, Version 3.0, Dept of the Air Force, Software Technology Support Center, 2000 Unit IV - Module Example Scenario Extension Continuation of the Mail Order Business Example A consultant recommends to the Owner that a Enterprise Resource Planning (ERP) tool should be used to implement his system He contacts several software consultants to see what they propose Unit IV - Module

29 Waterfall Traditional Development method follows a basic System Engineering process Benefits: Good when there are stable requirements provides structure to development Pitfalls: Doesn t allow prototyping No product to look at until completely done Not attuned to evolving needs System Requirements & Design CSCI Requirements Analysis Preliminary Design Waterfall Method (Also called Grand Design ) Detailed Design Code and CSU Test CSC Integration and Test CSCI Test System Test Quantitative Management of Software, Graduate School of Logistics and Acquisition Management, Air Force Institute of Technology, Air University, 1995 PRICE S Users Manual, Price Systems, Unit IV - Module Modeling Waterfall & Example Recommendation of first consultant Customer Management System CSCI 1 Develop and submit orders - CSC 1-5,000 SLOC - CSC 2 7,500 SLOC CSCI 2 Verify Order - CSC 1 3,000 SLOC CSCI 3 Approve Order - CSC 1 1,000 CSCI 4 Status Order - CSC 1 2,500 SLOC COTS Package 1 COTS Package 2 Most models treat Waterfall as basic approach so no special handling is required. Unit IV - Module Customer Management must be custom code; the straightforward, stable requirements make a single delivery possible Use COTS for remainder of the system; COTS included in the model to capture integration Quantitative Management of Software, Graduate School of Logistics and Acquisition Management, Air Force Institute of Technology, Air University,

30 Agile Iterative development which prioritizes evolution of requirements and solutions through collaboration of cross-functional teams Each iteration is a full software development cycle At the end of an iteration, the product can be reviewed and evaluated by the customer for feedback Agile development stresses team work and face-to-face communication Benefits: Adaptable to change AKA Scrum Prioritizes customer satisfaction and communication Focus on business need and business value "Agility XL", Schaaf, R.J., Systems and Software Sustainable development pace Technology Conference 2007, Tampa, FL, 2007 Pitfalls: Not structured enough for architecture design or re-design work May need to be combined with waterfall methodology to fit organizational needs Are Parametric Techniques Relevant for Agile Development Projects?, Minkiewicz, Arlene. PRICE Systems, Unit IV - Module NEW! Modeling Agile & Example Recommendation of second consultant Customer Management System Iteration 1 - CSC 1-6,500 SLOC Iteration 2 - CSC 1-6,300 SLOC Iteration 3 - CSC 1-6,200 SLOC Iteration 4 - CSC 1-6,100 SLOC Unit IV - Module The Agile approach means that planning sessions during development will determine the content of each iteration The team should know the pace of development and plan the content of the iteration accordingly The customer and development team will communicate closely during the development and planning process Are Parametric Techniques Relevant for Agile Development Projects?, Minkiewicz, Arlene. PRICE Systems, NEW! 30

31 Estimating Techniques Applied to Software Analogy Parametric 2 Unit IV - Module Analogy Analogy: Performing a comparative analysis of similar systems with adjustments to account for differences between new and analogous systems Example: Let s suppose for our mail order example that the owner chooses the First consultants Waterfall methodology solution The First consultant from Waterfall methodology must estimate his cost to set up the COTS software Using ACME Office and a new COTS package for human resources, accounting, and inventory management functions Consultant just completed a similar effort using 4 COTS products for a company twice the size of the Mail Order company Previous effort was: Set up software 280 hours Load Data 80 hours Implement at customer s site 100 hours Train users 20 hours 2 Unit IV - Module

32 Analogy Example Differences in new effort: 2 COTS packages reduces effort by 20% Data load same- company is smaller but data is not as automated Engineers say the implementation is expected to require 15% less effort because the company is smaller Calculations: Warning: The basis for this analogy is not strong. This is a YELLOW BOE at best. The comparison between the two programs has been simplified for purposes of the example Hours Set-up COTS product: 280 (280 * 0.2) = Data Load: Implementation: 100 (100 * 0.15) = Training: 20 (20 * 0.15) = Total 406 Given a labor rate of $100K/year: (406 Hrs / 1920 Hrs/Year) * $100,000 = $21,145 Unit IV - Module Parametric Most common estimating technique for software development Commercial models are parametric based Parametric based method is a mathematical relationship between a physical (size) or performance (reliability) parameter and the cost of a system Example: Mail order company continued First Consultant s waterfall solution Must estimate cost of custom code 5, , , , ,500 = 19,000 SLOC Vendor uses COCOMO II to estimate jobs has calibrated to his company E = (calibrated on similar efforts) EM = 0.38 (skilled development team) No adjustments were necessary for the code itself Labor rate is $16,000/month Unit IV - Module

33 Parametric Example - SLOC Mail order company continued First Consultant s waterfall solution Given: Must estimate cost of custom code (19,000 SLOC) Labor rate is $16,000/month Calculations: COCOMO II CER PM A Size Where: i 1 PM = Person Months A = Constant = 2.94 Size = KSLOC E = Sum of Scale Factors EM = Effort Multipliers Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, 2000 E n EM i Person Months = 2.94 * * 0.38 = Cost = * $16,000 = $382,643 Unit IV - Module Parametric Example - Schedule Mail order company continued First Consultant s waterfall solution Given: Must estimate schedule for development of custom code (19,000 SLOC) Person Months = E = 1, so F = Nominal schedule, SCED% = 1.0 Calculation: COCOMO II Schedule CER TDEV = [C*(PM NS ) (D+0.2*[E-B]) ]*SCED% Where: TDEV = Calendar time in months E = Sum of Scale factors C = 3.67 B = 0.91 D = 0.28 F = D X (E-B) PM NS = Person Months (un-scaled) SCED% = The amount of schedule compression or stretch-out as a percent of the nominal value Schedule Months = 3.67 * * 1.0 = 9.45 Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, 2000 Unit IV - Module

34 Software CER Development Software CER development is the same as hardware or other CER development processes Allows statistical inferences to be made Underlying assumption is that future reflects the past Expanded discussion in Modules 2, 3 and 8 Important reminders when developing your CERs Variable selection process very important Stay within the relevant range Normalize the data Test relationships Perform regression Unit IV - Module Challenges in Estimating Software System Definition Sizing and Tech Quality COTS Calibration Databases Growth and Demand Unit IV - Module

35 Challenges System Definition Obtaining System Definition Must work with experts Define notional system based on known requirements and include risk assessment for unknowns Definition often at a high level May include use of COTS software Talk to commercial vendors for inputs Multiple packages may be used For custom code, look at similar systems for functions that are required Assess need for both internal and external interfaces Refine definition over time as system takes shape Unit IV - Module Challenges Sizing and Tech Sizing Is An Estimate Too Use standard estimating methods 2 Rapid Technology Change Changes during the development process may have to be addressed COTS Upgrades May have to reintegrate Simple retest to complete redo or no change at all depends on COTS Development Tool Changes Newer tools may simplify effort (but still require learning) May force change to the development process Unit IV - Module

36 Challenges Quality Difficulty in Assessing Quality Don t know how good it is until you re done Good planning impacted by tight schedules and other constraints Software quality measures may help Defects Identified Defects Fixed Space Systems Cost Analysis Group Software Methodology Handbook, Version 1.0, June 1995, Failed Fixes Severity of Defects Location of Defect Degree of Cohesion and Coupling Requirements satisfied Depth of testing Adequacy of Documentation MTTD Errors McCabe s cyclomatic complexity Unit IV - Module Challenges COTS 14 Using Commercial Off-the-Shelf (COTS) Software No code visibility Warning: Difficult to customize no source code COTS Cheap! Effort dependent on the software architecture Might be too rigid to handle changing requirements Assumes many users will find errors - need additional testing Upgrades to COTS may force reintegration with custom code Support costs for custom code may be affected and will vendor need support for COTS Still must perform requirements definition, design, and test of the overall system Dealing with licensing, royalties, incompatibilities between packages, lack of source code and understanding package Estimation of COTS integration not mature Unit IV - Module

37 Challenges Calibration Calibration of models Most models built on industry averages therefore calibration may increase accuracy Adjusts relationships/values to achieve 3 representative known outcomes Understand how your model calibrates Must collect cost, technical and programmatic data Check content of actual data vs. content of model Generally models have a calibration mode but may need to tweak the model Calibration of models must be done with care but is generally an improvement over default values Unit IV - Module Challenges Databases Database Development Most models don t address major database development Must estimate outside of model using other 2 estimating techniques Consider Number of feeder systems Number of data elements Number of uses Number of users COTS database software for development and feeder systems Unit IV - Module

38 Challenges Growth and Demand Requirements and Code Growth Delivered project is bigger than estimated Increase driven by: Poor understanding of requirements initially New requirements added during development Underestimate of required SLOC Code reuse optimism Key is to know the track record and account for expected growth Supply and Demand of Labor Warning: Beware requirements creep! Affects personnel availability and cost of qualified personnel Unit IV - Module Software Cost Estimating Summary Understanding software cost estimation is critical because software is part of almost every estimate Software cost estimating is in many ways similar to hardware estimating There are a variety of software development approaches that can affect development cost and must be modeled accordingly to estimate Analogy and Parametric are commonly used to estimate software development costs There are a number of commercial parametric models available to estimate software costs Software provides a number of specific challenges for the estimator Unit IV - Module

39 Resources [Pressman] Software Engineering, A Practitioner s Approach, Third Edition, Roger S. Pressman, McGraw Hill, Inc., 1992 [Boehm 81] Software Engineering Economics, Barry W. Boehm, Prentice Hall, 1981 [Boehm 2000] Software Cost Estimation with COCOMO II, Boehm et al., Prentice Hall PTR, 2000 [ISPA 1999] Spring 2 nd Edition Joint Industry/Government PARAMETRIC ESTIMATING HANDBOOK, [GSAM 2000] Guidelines for Successful Acquisition and Management of Software Intensive Systems: Weapon Systems, Command and Control Systems, Management Information Systems, Version 3.0, Dept of the Air Force, Software Technology Support Center, 2000 [AFIT] Quantitative Management of Software, Graduate School of Logistics and Acquisition Management, Air Force Institute of Technology, Air University, 1995 [IFPUG] International Function Point Users Group, [Taylor] Object-Oriented Technology: A Manager s Guide, David A. Taylor, Addison-Wesley, 1990 [Cox] Object-Oriented Programming: An Evolutionary Approach, Brad J. Cox, Addison-Wesley, 1987 SEER-SEM, Galorath Inc., [STSC] Crosstalk The Journal of Defense Software Engineering, Unit IV - Module Resources [Reifer] Quantifying the Debate: Ada vs. C++, Donald J. Reifer, Crosstalk: The Journal of Defense Software Engineering, Vol. 9, Number 7, July 1996 [Jensen] Software Estimating Model Calibration, Randall W. Jensen, Crosstalk: The Journal of Defense Software Engineering, Vol. 14, Number 7, July 2001 [Jones 1] Applied Software Measurement: Assuring Productivity and Quality, 2 nd ed, Capers Jones, McGraw Hill, 1996 [Jones 2] Estimating Software Costs, T. Capers Jones, McGraw Hill, 1998 COCOMO II, [PRICE S] PRICE S Users Manual, Price Systems, [MIL STD 498]Military Standard 498, Software Development and Documentation, December 1994 [IEEE] IEEE/EIA , IEEE/EIA Guide, Industry Implementation of International Standard ISO/IEC 12207; 1995, Standard for Information Technology, Software Life Cycle Processes Implementation Consideration, April 1998 [MIL-HDBK-881A] Department of Defense Handbook Work Breakdown Structures for Defense Materiel Items, July, 2005 [SEI-CMM] Capability Maturity Model for Software, Version 1.1, Paulk, Mark C. et.al., Software Engineering Institute, Carnegie Mellon University, February 1993 [Schaaf] "Agility XL", Schaaf, R.J., Systems and Software Technology Conference 2007, Tampa, FL, 2007 Are Parametric Techniques Relevant for Agile Development Projects?, Minkiewicz, Arlene. PRICE Systems, Unit IV - Module

40 Related and Advanced Topics Software Data Collection Rules of Thumb Off-The-Shelf Models Software and AIS State of the Art Estimating Other Dev Methodologies Firmware Unit IV - Module Software Resources Data Reports (SRDRs) Provide software information across programs Provide size, effort, schedule, other descriptive development data DoD s only standard centralized approach to SW data collection Used to obtain both the estimated and actual characteristics of new software developments or upgrades Both the Government program office and, later on after contract award, the software contractor submit this report For contractors, this report constitutes a contract data deliverable that formalizes the reporting of software metric and resource data Not intended as a project management device to track software development progress The SRDR is divided into three reports, Initial/Final Government Report, Initial Developer Report, Final Developer Report SRDR is Required for: All major contracts and subcontracts, regardless of contract type For any element with a projected effort greater than $25M Contractors developing/producing software elements within ACAT IA, ACAT IC and ACAT ID programs Understanding the Software Resource Data Report Requirements, 5 June 2012, Unit IV - Module

41 Rules of Thumb Develop your own metrics Use government or industry standards from literature in interim Make sure rules are applicable to your environment Age of rule Software language used Purpose of software Rules of Thumb Cost per SLOC Cost per Function Point Unit IV - Module Cost Per SLOC Application Domain Ada 83 Ada 95 C C++ 3GL Domain Norm Command and Control Commercial 50 * Military 75 * Commercial Products Information Systems Commercial * * Military Telecommunications Commercial 55 * Military 60 * Weapons Systems Airborne and Spaceborne 150 * 175 * Ground Based 80 * *=not enough data available Dollar Cost per Delivered Source Line of Code (1995) Quantifying the Debate: Ada vs. C++, Donald J. Reifer, Crosstalk: The Journal of Defense Software Engineering, Vol. 9, Number 7, July 1996 Unit IV - Module

42 Cost Per Function Point Average Cost per Function Point (Salary + Burden), Dollars Function Points End User MIS Outsource Commercial Systems Military Average ,008 3,291 1, ,215 1,000 1,575 5,119 1, ,475 1,540 2,016 6,581 2,134 1, ,642 2,376 1,920 2,587 8,336 3,372 10, ,554 3,861 2,944 3,553 11,232 4, , ,104 6,426 4,092 5,897 16,161 7,336 Average 232 1,684 2,671 2,049 2,773 8,453 3,389 Median 240 1,248 1,925 1,730 2,302 7,459 2,753 Mode 180 1,022 1,689 1,487 2,059 6,679 2,587 Applied Software Measurement: Assuring Productivity and Quality, 2 nd ed, Capers Jones, McGraw Hill, 1996 Unit IV - Module Off-The-Shelf Models COCOMO II TruePlanning SEER - SEM Unit IV - Module

43 COCOMO II 3 Constructive Cost Model (COCOMO) By Barry Boehm and others at the University of Southern California (USC) Center for Software Engineering (CSE) First presented in Software Engineering Economics in 1981 Updated in 2000 to COCOMO II in Software Cost Estimation with COCOMO II Website is Unit IV - Module COCOMO II Inputs/Outputs Inputs - Program size (SLOC or function points) - Similarity of the product to previous efforts - Flexibility allowed wrt other reqts, interfaces - Storage constraints - Thoroughness of the design effort - Volatility of associated H/W and software - Risk elimination - Analyst capability - Development team cohesion - Programmer capability - Maturity of the software development process - Continuity of the personnel on the project - Required product reliability - Personnel experience in the application - Size of the database - Personnel experience w platform - Complexity of software operations - Personnel experience w language and tools - Need for re-usability - Use of software development tools - Degree of documentation required - Development locations - Execution time constraints - Development schedules Outputs Development effort in person months and schedule in months Unit IV - Module

44 COCOMO II Adjustments Calibration Consolidating or eliminating statistically redundant parameters Pitfalls Add cost drivers not in the model Calibrate to existing actuals Constant A and Exponent E can be calibrated Recommend 5 data points for constant only and 10 if adjust Exponent also Use regression analysis Over-reliance on model Software Estimating Model Calibration, Randall W. Jensen, Crosstalk: The Journal of Defense Software Engineering, Vol. 14, Number 7, July Unit IV - Module Warning: If coefficients are changed through calibration, Effort Multipliers and the model as a whole need to be re-validated 3 TruePlanning 3 Owned by PRICE Systems of Mt. Laurel, New Jersey Automated model purchased for an annual license fee TrueAnalyst Model Builder Catalog Collection of models (TRUE S, TRUE IT, etc.) TruePlanning creates the cost estimate Website is Unit IV - Module